Post-tuberculosis lung impairment: systematic review and meta-analysis of spirometry data from 14 621 people
Bibliographic record
Abstract
Background A substantial proportion of tuberculosis patients remain with pulmonary symptoms and reduced physical capacity despite successful treatment. We performed a systematic review to analyse the burden of post-tuberculosis lung impairment measured by lung function testing. Methods We searched the PubMed database for articles published between database inception and November 2020 and performed meta-analyses to estimate the prevalence, type and severity of lung impairment among drug-susceptible and multidrug-resistant tuberculosis survivors. Methodological quality of included studies was assessed using the Newcastle–Ottawa scale. Results 54 articles were included in this review. For subjects with former drug-susceptible tuberculosis, the combined estimated mean was 76.6% (95% CI 71.6–81.6) of predicted for forced expiratory volume in 1 s (FEV 1 ) and 81.8% (95% CI 77.4–86.2) for forced vital capacity (FVC). In former patients with multidrug-resistant tuberculosis, it was 65.9% (95% CI 57.1–74.7) for FEV 1 and 76.0% (95% CI 66.3–85.8) for FVC, respectively. The analysis of impairment types in former patients with drug-susceptible and multidrug-resistant tuberculosis showed that 22.0% versus 19.0% had obstructive, 23.0% versus 22.0% restrictive and 15.0% versus 43.0% had mixed impairment type, respectively. In the majority of studies, at least 10–15% of tuberculosis survivors had severe lung impairment. Conclusions This systematic review showed long-term abnormal spirometry results in a significant proportion of tuberculosis survivors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.027 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".